Data extraction using AI refers to the automatic identification and extraction of relevant information from unstructured or semi-structured data sources, such as text documents or images.
One example of using AI for data extraction is the combination of Natural Language Processing (NLP) and Computer Vision (CV) to extract data from invoices. NLP identifies the relevant text fields such as vendor name, invoice number, and date, while CV locates the exact location of these fields on the invoice image. This automated approach saves time and effort compared to manual data entry, and the extracted data is stored in a structured format for further analysis or processing.
Data extraction currently presents as a more effective alternative to Optical Character Recognition (OCR). Optical Character Recognition is a technology used to convert scanned images of text into machine-readable text. While OCR can be useful for extracting text from documents, it has some limitations when it comes to extracting structured data from unstructured or semi-structured sources such as invoices.
This is why the combination of NLP and CV for data extraction offers several advantages over OCR. First, NLP and CV can work together to extract specific pieces of information from a document, such as a vendor name, invoice number, and date, rather than just extracting all the text. This means that the extracted data can be more accurate and relevant, saving time and effort during the validation process.
What Is Optical Character Recognition (OCR): Its Working, Limitations, and Alternatives
Transforming Business Performance through Effective ML Model Deployment
AI in Fintech: The Cutting-Edge Technology Driving Future of Financial Services
Data Extraction Software for Fintech. No More Traditional OCR that Is Prone to Errors
Artificial Intelligence in the Nonprofit Sector
AI in GovTech: White-Label AI Solution for Data Extraction
Artificial Intelligence in Healthcare. Achieve More by Doing Less
AI in Insurance: Innovate Traditional Paperway
AI in FinTech
AI in FinTech refers to the seamless integration of AI technologies into the fabric of financial services, enhancing accessibility, convenience, and efficiency.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of computer science that enables machines to interpret and comprehend human language for various tasks.
Computer Vision (CV)
Computer vision (CV) is a type of artificial intelligence that uses deep learning to analyze visual data for its further application.